from collections.abc import Sequence
from typing import Any, final

from qdrant_client import AsyncQdrantClient, models

from .config import Settings
from .models import SearchRow


@final
class QdrantEngine:
    def __init__(self) -> None:
        self.settings = Settings()  # type: ignore[reportCallIssue]
        self.client = AsyncQdrantClient(
            url=self.settings.url, api_key=self.settings.api_key
        )

    async def semantic_search(
        self,
        embedding: Sequence[float] | models.NamedVector,
        collection: str,
        limit: int = 10,
        conditions: Any | None = None,
        threshold: float | None = None,
    ) -> list[SearchRow]:
        points = await self.client.search(
            collection_name=collection,
            query_vector=embedding,
            query_filter=conditions,
            limit=limit,
            with_payload=True,
            with_vectors=False,
            score_threshold=threshold,
        )

        return [
            SearchRow(chunk_id=str(point.id), score=point.score, payload=point.payload)
            for point in points
            if point.payload is not None
        ]